Deep Learning Applications, Volume 4

Dr. M. Arif Wani is currently a Professor at the University of Kashmir, having previously served as a Professor at California State University Bakersfield. He completed his M. Tech. in Computer Technology at the   Indian Institute of Technology, Delhi, and his Ph.D. in Computer Vision at Cardiff University, UK. His research interests are in the area of machine learning, with a focus on neural networks, deep learning, inductive learning, and support vector machines, and with application to areas that include computer vision, pattern recognition, classification, prediction and analysis of gene expression datasets. He has published many papers in reputed journals and conferences in these areas. Dr. Wani has co-authored the book ‘Advances in Deep Learning’, co-edited many books in ‘Machine Learning and Applications’ and ‘Deep Learning Applications’. He is a member of many academic and professional bodies.Dr. Vasile Palade is currently a Professor of Artificial Intelligence and Data Science at Coventry University, UK. He previously held several academic and research positions at the University of Oxford - UK, University of Hull - UK, and the University of Galati - Romania. His research interests are in the area of machine learning, with a focus on neural networks and deep learning, and with main application to computer vision, social network data analysis and web mining, autonomous driving, smart cities, health, among others. Prof. Palade is author and co-author of more than 200 papers in journals and conference proceedings as well as several books on machine learning and applications. He is an Associate Editor for several reputed journals, such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Knowledge and Information Systems. He has delivered keynote talks to international conferences on machine learning and applications. Dr. Vasile Palade is an IEEE Senior Member.

• Identification of Human Papillomavirus from Super Resolution Microscopic Images Generated Using Deep Learning Architectures.- Evaluation of Sequential and Temporally-Embedded Deep Learning Models for Health Outcome Prediction.- Transfer Learning for Depression Screening from Follow-up Clinical Interview Questions.- Early Mental Health Uncovering with Short Scripted and Unscripted Voice Recordings.- A Comprehensive Analysis of Aspect Oriented Suggestion Extraction from Online Reviews.